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All Journal Populis : Jurnal Sosial dan Humaniora Jurnal Pustaka Ilmiah
Wardani, Hesti Ari
Unknown Affiliation
Education Library & Information Science Social Sciences

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Pemetaan Konseptual Kajian Feminisme melalui Analisis Bibliometrik Visual terhadap Literatur Tahun 2015–2025 Wardani, Hesti Ari; Yuadi, Imam
Populis : Jurnal Sosial dan Humaniora Vol. 10 No. 1 (2025)
Publisher : Universitas Nasional

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Abstract

This study aims to map the conceptual structure of feminist scholarship through a visual bibliometric approach using data from Google Scholar, collected via the Publish or Perish software and analyzed with VOSviewer. A total of 1,000 academic articles published between 2013 and 2023 were analyzed. Three types of visualizations—density, overlay, and network—were employed to identify thematic density, temporal trends, and keyword co-occurrence within the literature on feminism. The results show that terms such as second wave feminism, radical feminism, and popular feminism dominate the field and serve as the foundation of contemporary feminist discourse. Meanwhile, terms such as white feminism, transnational feminism, and methodology have recently emerged, indicating a shift in research interest toward more reflective, intersectional, and global feminist frameworks. The network visualization reveals distinct thematic clusters that illustrate the complexity and diversity of feminist approaches. These findings suggest that feminist scholarship is evolving from ideological roots toward more methodological and transnational reflexivity. This study contributes to the intellectual mapping of feminism and provides a basis for future interdisciplinary and context-specific feminist research.
Analisis Visual dan Machine Learning untuk Mengukur Validitas Dokumen Akademik Perpustakaan: Studi pada Data Turnitin Wardani, Hesti Ari; Yuadi, Imam
Jurnal Pustaka Ilmiah Vol 11, No 1 (2025): Jurnal Pustaka Ilmiah
Publisher : Universitas Sebelas Maret Library

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jpi.v11i1.98828

Abstract

The issue of plagiarism in academic works is a major concern in higher education as it can undermine academic integrity. This study aims to analyze the distribution of Turnitin results in academic library documents from various study programs at Universitas Nasional, Jakarta. Using a data visualization approach and machine learning algorithms, this research explores the relationship between Turnitin scores and document validity status. The methods used include data visualization through Scatter Plots, Violin Plots, and Box Plots, with these visualizations utilizing Orange Data Mining as the data processing method. Additionally, a logistic regression algorithm is applied to classify documents based on Turnitin scores. Furthermore, the Chi-Square statistical test is implemented to evaluate the significance of the relationship between Turnitin results and document validity status. The findings of this study indicate that Turnitin scores exhibit significant distribution differences among study programs, with notable disparities between valid and invalid documents. Documents from certain study programs tend to have dominant scores in the 20-50% range, which serves as a critical threshold in determining document validity. This study provides in-depth insights into the patterns of academic document validity and offers a data-driven approach to improving the quality of academic evaluation in higher education. Additionally, this research is expected to serve as a foundation for academic policies in strengthening plagiarism detection systems, increasing transparency in evaluation, and promoting the development of more accurate and efficient document validation methods. However, this study has limitations regarding the scope of data used, particularly in terms of study program representation and external factors that may influence Turnitin scores. Further research is needed to examine pedagogical aspects and academic policies that contribute to variations in Turnitin scores across different study programs.
Co-Authors Imam Yuadi